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Stochastic calculus

Stochastic calculus is a branch of mathematics that operates on stochastic processes. It allows a consistent theory of integration to be defined for integrals of stochastic processes with respect to stochastic processes. This field was created and started by the Japanese mathematician Kiyosi Itô during World War II.

The best-known stochastic process to which stochastic calculus is applied is the Wiener process (named in honor of Norbert Wiener), which is used for modeling Brownian motion as described by Louis Bachelier in 1900 and by Albert Einstein in 1905 and other physical diffusion processes in space of particles subject to random forces. Since the 1970s, the Wiener process has been widely applied in financial mathematics and economics to model the evolution in time of stock prices and bond interest rates.

The main flavours of stochastic calculus are the Itô calculus and its variational relative the Malliavin calculus. For technical reasons the Itô integral is the most useful for general classes of processes, but the related Stratonovich integral is frequently useful in problem formulation (particularly in engineering disciplines). The Stratonovich integral can readily be expressed in terms of the Itô integral, and vice versa. The main benefit of the Stratonovich integral is that it obeys the usual chain rule and therefore does not require Itô's lemma. This enables problems to be expressed in a coordinate system invariant form, which is invaluable when developing stochastic calculus on manifolds other than Rn. The dominated convergence theorem does not hold for the Stratonovich integral; consequently it is very difficult to prove results without re-expressing the integrals in Itô form.

Itô integral edit

The Itô integral is central to the study of stochastic calculus. The integral   is defined for a semimartingale X and locally bounded predictable process H. [citation needed]

Stratonovich integral edit

The Stratonovich integral or Fisk–Stratonovich integral of a semimartingale   against another semimartingale Y can be defined in terms of the Itô integral as

 

where [XY]tc denotes the quadratic covariation of the continuous parts of X and Y. The alternative notation

 

is also used to denote the Stratonovich integral.

Applications edit

An important application of stochastic calculus is in mathematical finance, in which asset prices are often assumed to follow stochastic differential equations. For example, the Black–Scholes model prices options as if they follow a geometric Brownian motion, illustrating the opportunities and risks from applying stochastic calculus.

Stochastic integrals edit

Besides the classical Itô and Fisk–Stratonovich integrals, many different notion of stochastic integrals exist such as the Hitsuda–Skorokhod integral, the Marcus integral, the Ogawa integral and more.

See also edit

References edit

  • Fima C Klebaner, 2012, Introduction to Stochastic Calculus with Application (3rd Edition). World Scientific Publishing, ISBN 9781848168312
  • Szabados, T. S.; Székely, B. Z. (2008). "Stochastic Integration Based on Simple, Symmetric Random Walks". Journal of Theoretical Probability. 22: 203–219. arXiv:0712.3908. doi:10.1007/s10959-007-0140-8. Preprint

stochastic, calculus, this, article, includes, list, references, related, reading, external, links, sources, remain, unclear, because, lacks, inline, citations, please, help, improve, this, article, introducing, more, precise, citations, august, 2011, learn, w. This article includes a list of references related reading or external links but its sources remain unclear because it lacks inline citations Please help improve this article by introducing more precise citations August 2011 Learn how and when to remove this message Stochastic calculus is a branch of mathematics that operates on stochastic processes It allows a consistent theory of integration to be defined for integrals of stochastic processes with respect to stochastic processes This field was created and started by the Japanese mathematician Kiyosi Ito during World War II The best known stochastic process to which stochastic calculus is applied is the Wiener process named in honor of Norbert Wiener which is used for modeling Brownian motion as described by Louis Bachelier in 1900 and by Albert Einstein in 1905 and other physical diffusion processes in space of particles subject to random forces Since the 1970s the Wiener process has been widely applied in financial mathematics and economics to model the evolution in time of stock prices and bond interest rates The main flavours of stochastic calculus are the Ito calculus and its variational relative the Malliavin calculus For technical reasons the Ito integral is the most useful for general classes of processes but the related Stratonovich integral is frequently useful in problem formulation particularly in engineering disciplines The Stratonovich integral can readily be expressed in terms of the Ito integral and vice versa The main benefit of the Stratonovich integral is that it obeys the usual chain rule and therefore does not require Ito s lemma This enables problems to be expressed in a coordinate system invariant form which is invaluable when developing stochastic calculus on manifolds other than Rn The dominated convergence theorem does not hold for the Stratonovich integral consequently it is very difficult to prove results without re expressing the integrals in Ito form Contents 1 Ito integral 2 Stratonovich integral 3 Applications 4 Stochastic integrals 5 See also 6 ReferencesIto integral editMain article Ito calculus The Ito integral is central to the study of stochastic calculus The integral H d X displaystyle int H dX nbsp is defined for a semimartingale X and locally bounded predictable process H citation needed Stratonovich integral editMain article Stratonovich integral The Stratonovich integral or Fisk Stratonovich integral of a semimartingale X displaystyle X nbsp against another semimartingale Y can be defined in terms of the Ito integral as 0 t X s d Y s 0 t X s d Y s 1 2 X Y t c displaystyle int 0 t X s circ dY s int 0 t X s dY s frac 1 2 left X Y right t c nbsp where X Y tc denotes the quadratic covariation of the continuous parts of X and Y The alternative notation 0 t X s Y s displaystyle int 0 t X s partial Y s nbsp is also used to denote the Stratonovich integral Applications editAn important application of stochastic calculus is in mathematical finance in which asset prices are often assumed to follow stochastic differential equations For example the Black Scholes model prices options as if they follow a geometric Brownian motion illustrating the opportunities and risks from applying stochastic calculus Stochastic integrals editBesides the classical Ito and Fisk Stratonovich integrals many different notion of stochastic integrals exist such as the Hitsuda Skorokhod integral the Marcus integral the Ogawa integral and more See also edit nbsp Mathematics portal Ito calculus Ito s lemma Stratonovich integral Semimartingale Wiener processReferences editFima C Klebaner 2012 Introduction to Stochastic Calculus with Application 3rd Edition World Scientific Publishing ISBN 9781848168312 Szabados T S Szekely B Z 2008 Stochastic Integration Based on Simple Symmetric Random Walks Journal of Theoretical Probability 22 203 219 arXiv 0712 3908 doi 10 1007 s10959 007 0140 8 Preprint Retrieved from https en wikipedia org w index php title Stochastic calculus amp oldid 1214491887, wikipedia, wiki, book, books, library,

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